Face Recognition Software Development
INDUSTRY
AI
SERVICE
Computer Vision
CLIENT
R&D
R&D: Face Recognition Software Development
"Waverley Software R&D team developed a face recognition system using Computer Vision and Deep Learning techniques."
Waverley Software R&D team developed a face recognition system using Computer Vision and Deep Learning techniques.
R&D
Discovery
Our R&D department is currently working on a face detection system that will recognize people when they enter the room and address them with an audible personalized greeting.The goal of the project is to create a Computer Vision algorithm and train it to detect a human face on the basis of footage from surveillance cameras. Once detected, the face is matched with the identity of a specific person whose data is in the system, which then generates action items such as a personalized greeting.
What We Delivered
First we gathered all the corresponding vectors we used to create the database and assigned them to the people to whom they belong. To accomplish that we applied a Deep Learning algorithm that generates face embeddings to be compared with the vector embeddings already in the database. When a match is detected, the system sends a notification and launches an action item such as “play a personalized greeting” or “open the door.”
In order to cope with the poor quality video extracted from surveillance cameras and “clean up” the visual data, we used Computer Vision algorithms and various optical filters to improve contrast, remove shades, add more exposure,etc.
To optimize the system, we applied a high-speed detector for the initial processing and a slow-speed detector that requires more resources from the system but provides more accurate results. This model filtered the videos to separate footage that contained human faces from footage that did not. This combined, pre-filtering approach was introduced to prevent overloading the recognition server.
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